About pa module introduction

You can use the pa.DataFrame constructor to create a pa data frame from a pandas data frame: pdf = pa.DataFrame(pandas_df)

You can use the pdf.columns and pdf.rows attributes to access the columns and rows of a pa data frame as lists of strings and integers, respectively. You can also use the pdf[col] and pdf[row] syntax to access a specific column or row as a pa series.

You can use the standard arithmetic operators (+, -, *, /, **) to perform element-wise operations on pa data frames and series. You can also use the pdf.apply(func) and ps.apply(func) methods to apply a custom function to each element of a pa data frame or series.

You can use the pdf.to_csv(filename) and pa.read_csv(filename) methods to save and load pa data frames to and from CSV files. You can also use the pdf.to_pickle(filename) and pa.read_pickle(filename) methods to save and load pa data frames to and from pickle files.